The heat transfer between a nanotip and its substrate is extremely complex but is a key factor in determining the measurement accuracy in tip-assisted nanomanufacturing and thermometry. In this work, the heat transfer from the nanotip to the substrate during sliding is investigated using molecular dynamics simulations. Interfacial interaction and bond formation are analyzed during the sliding process. The results show that the increase of vertical force would greatly improve the interface thermal conductance between the nanotip and the substrate. It is found that more bonds are formed and there are larger contact areas at the interface. In addition, we found that the thermal conductivity of the nanotip is another obstacle for heat transfer between the tip and substrate and it is greatly limited by the nanotip diameter near contact which is close to or even smaller than the phonon mean free path. Meanwhile, the dynamic formation and breakage of the covalent bonds during the sliding could gradually smoothen the tip apex and enhance the thermal transport at the interface. This work provides guidance for the thermal design of a nanotip-substrate system for nanoscale thermal transport measurements.

It is desirable to fabricate materials with adjustable physical properties that can be used in different industrial applications. Since the property of a material is highly dependent on its inner structure, the understanding of structure–property correlation is critical to the design of engineering materials. 3D printing appears as a mature method to effectively produce micro-structured materials. In this work, we created different stainless-steel microstructures by adjusting the speed of 3D printing and studied the relationship between thermal property and printing speed. Our microstructure study demonstrates that highly porous structures appear at higher speeds, and there is a nearly linear relationship between porosity and printing speed. The thermal conductivity of samples fabricated by different printing speeds is characterized. Then, the correlation between porosity, thermal conductivity, and scanning speed is established. Based on this correlation, the thermal conductivity of a sample can be predicted from its printing speed. We fabricated a new sample at a different speed, and the thermal conductivity measurement agrees well with the value predicted from the correlation. To explore thermal transport physics, the effects of pore structure and temperature on the thermal performance of the printed block are also studied. Our work demonstrates that the combination of the 3D printing technique and the printing speed control can regulate the thermophysical properties of materials.

An automatic reading of text from an identity (ID) card image has a wide range of social uses.In this paper, we propose a novel method for Chinese text recognition from ID card images taken by cellphone cameras.The paper has two main contributions: (1) A synthetic data engine based on a conditional adversarial generative network is designed to generate million-level synthetic ID card text line images, which can not only retain the inherent template pattern of ID card images but also preserve the diversity of synthetic data.(2) An improved convolutional recurrent neural network (CRNN) is presented to increase Chinese text recognition accuracy, in which DenseNet substitutes VGGNet architecture to extract more sophisticated spatial features.The proposed method is evaluated with more than 7000 real ID card text line images.The experimental results demonstrate that the improved CRNN model trained only on the synthetic dataset can increase the recognition accuracy of Chinese text in cellphone-acquired low-quality images.Specifically, compared with the original CRNN, the average character recognition accuracy (CRA) is increased from 96.87 to 98.57% and the line recognition accuracy (LRA) is increased from 65.92 to 90.10%.

Vertically aligned arrays of carbon nanotubes (CNTs) are attractive for a wide range of macroscopic applications which can exploit the remarkable properties of individual nanotubes. In this work, an abnormal behavior of CNT bundles in heat conduction is discovered under the transient electro-thermal characterization. The measured voltage change over the sample shows a dual-pace thermal response (DTR), which could not be fitted using a single thermal diffusivity heat transfer model. Instead, two thermal diffusivities are determined from the DTR phenomenon. Three rounds of cryogenic experiments are conducted to investigate the physics behind DTR phenomenon. It starts to emerge when the temperature is reduced to a certain level. After two rounds of cryogenic experiments, the DTR phenomenon becomes permanent from 295 K to 10 K. The nano-scale structure separation induced by the increased thermal strain leads to macroscale structure separation, which results in two parallel heat conduction paths responsible for the DTR phenomenon. By building a new parallel heat transfer model taking both the transient and steady-state electrical and thermal response into consideration, the area ratio of separated CNTs is determined. This result uncovers the existence of coiled morphology and nano-structure evolution of CNTs under cryogenic state and its effect on thermal and electrical transport, especially on their transient behaviors. Knowledge of the thermal transport in these CNTs arrays is important considering the fact that transient thermal response strongly affects their mechanical, optical, and electrical behaviors.

针对存在大角度透视变形的集装箱图像,提出一种新的集装箱箱号识别方法.首先对图像进行透视变换校正,然后利用深度卷积神经网络模型定位并识别出集装箱图像中的26个大写英文字母和10个阿拉伯数字,最后利用集装箱箱号的先验知识,通过级联决策规则从候选字符集中识别出集装箱箱号.此方法应用于重庆港集装箱1 035张实景图像,箱号识别精度达97％,基于NVIDIA GeForce GTX1080图形处理器加速的箱号识别速度为每秒2～5帧.

鉴于由于类型、规模、自然环境等的差异,不同港口在高分遥感影像上表现出的形状、方向、纹理等特征往往具有较大差异,因而利用低层特征在高分遥感影像上进行港口检测面临较大挑战,提出一种利用非监督提取算法提取高分遥感影像中层特征用于港口检测的方法.该方法通过对大量样本的自主学习,提取能够识别港口的可分图斑作为中层特征表达,再用词袋模型构建基于可分图斑的特征向量,并利用SVM分类器检测港口.最后,探讨了可分图斑提取算法中相关参数设置对检测结果的影响,并利用测试影像集对该方法进行了验证,结果表明其检测正确率达97.5％.

A method of ship detection in high-resolution remote sensing images using mixture of deformable part models(DPMs) is proposed in this paper.The method is robust to size difference by constructing multi-scale histogram of oriented gradients (HOG) feature pyramids.Deformable part models are introduced to deal with the deformation of the key parts of ships.And a sliding window detection strategy is adopted to separate the clustered ships.Considering that HOG features are orientation-sensitive,improved training and detection methods are also proposed.In the training phase,all the samples are rotated to the same direction for parameter learning to reduce the number of templates.In the detection phase,the regions of interest are rotated to a specific direction to implement template matching.The experiments of ship detection in GaoFen-2 high-resolution remote sensing images are carried out.It is shown that the proposed method is effective.

Heat conduction and convection are coupled effects in thermal transport of low-dimensional materials especially at micro/nanoscale. However, the parallel measurement is a challenge due to the limitation of characterization pathways. In this work, we report a method to study conductive and convective thermal transport of micro/nanowires simultaneously by using steady-state Joule-heating and Raman mapping. To examine this method, the carbon nanotubes (CNTs) fiber (36 μm in diameter) is characterized and its temperature dependence of thermal properties including thermal conductivity and convection coefficient in ambient air is studied. Preliminary results show that thermal conductivity of the CNTs fiber increases from 26 W/m K to 34 W/m K and convection coefficient decreases from 1143 W/m2 K to 1039 W/m2 K with temperature ranging from 312 to 444 K. The convective heat dissipation to the air could be as high as 60% of the total Joule heating power. Uncertainty analysis is performed to reveal that fitting errors can be further reduced by increasing sampling points along the fiber. This method features a fast/convenient way for parallel measurement of both heat conduction and convection of micro/nanowires which is beneficial to comprehensively understanding the coupled effect of micro/nanoscale heat conduction and convection.

提出了一种基于人工免疫算法的光学影像和SAR影像配准方法,该方法从影像上的面状地物入手,仅从识别性较好的光学影像上提取面状地物,先随机给定一组配准参数,将光学影像上面状地物的坐标经仿射变换获得新的坐标,以转换后新坐标在SAR影像上对应区域的均质性为评价标准,并利用人工免疫算法对配准参数进行优化,从而得到影像配准结果.最后,利用WorldView-2和RadarSat-2影像的配准实验验证该方法的有效性,结果表明该方法配准精度可优于2像素.

Spatial confinement is found effective in improving the sensitivity of laser-induced breakdown spectroscopy (LIBS). This work reports on the physics of shock wave spatial confinement via atomistic modeling. Reflection-induced atomic collision/friction near the wall reduces the shock wave velocity close to zero and remarkably increases the local temperature (∼218 K) and pressure. As a result, the reflected ambient gas expands quickly toward the plume and compresses it. The temperature of the plume goes up significantly in the compression process: from 89 to 132 K. The lifetime of the plume is also boosted dramatically, from 480 ps to ∼1800 ps.

This paper uses ALOS multi -spectral images and CV models to extract coastlines on three different types coast of Shan -dong, which are artificial coast , sandy coast and muddy coast .To compare the extraction effect on different coast images , the same type coast image was divided into near -infrared image, 421 color composite image, NDWI image and PCA image, and finally t buffer analysis was used for comparing the accuracy .As analyzed, for artificial coast, and sandy coast, in a pixel buffer, more than 80%ex-traction accuracy can be achieved and within two pixels the result can reach to more than 95%;for muddy coast , four kinds of feature images all work badly , only NDWI image can reach to 87%within two buffers;overall, NDWI image works best .

提出了一种基于TerraSAR-X影像的桥梁提取和参数计算方法.首先使用Gaobor纹理、共生矩阵纹理和多分辨率影像分割获取桥梁的兴趣区,基于快速直线段检测算子(LSD)检测桥梁的方向,最后利用雷达成像参数和多次回波模型计算桥梁的方向、宽度、水面高度、桥体厚度.试验结果表明了该方法的有效性.

Under the background of implementing the excellent engineer 's education training plan in China , the curriculum planning for undergraduate students , whose specialty are Geographic Information System in the college of surveying and Geo -Informatics Tongji University, is analyzed in this paper .In order to improve the teaching effectiveness , a novel remote sensing platform , called GigaPan system, is introduced to the experimental teaching in urban remote sensing course .Finally, the teaching effectiveness is discussed and concluded .

Optical image is rich in spectral information, while SAR instrument can work in both day and night and obtain images through fog and clouds. Combination of these two types of complementary images shows the great advantages of better image interpretation. Image registration is an inevitable and critical problem for the applications of multi-source remote sensing images, such as image fusion, pattern recognition and change detection. However, the different characteristics between SAR and optical images, which are due to the difference in imaging mechanism and the speckle noises in SAR image, bring great challenges to the multi-source image registration. Therefore, a novel image registration algorithm based on the virtual points, derived from the corresponding region features, is proposed in this paper. Firstly, image classification methods are adopted to extract closed regions from SAR and optical images respectively. Secondly, corresponding region features are matched by constructing cost function with rotate invariant region descriptors such as area, perimeter, and the length of major and minor axes. Thirdly, virtual points derived from corresponding region features, such as the centroids, endpoints and cross points of major and minor axes, are used to calculate initial registration parameters. Finally, the parameters are corrected by an iterative calculation, which will be terminated when the overlap of corresponding region features reaches its maximum. In the experiment, WordView-2 and Radasat-2 with 0.5m and 4.7m spatial resolution respectively, obtained in August 2010 in Suzhou, are used to test the registration method. It is shown that the multi-source image registration algorithm presented above is effective, and the accuracy of registration is up to pixel level.

This article compares the domestic configurations of the boiler feed-water pump for 1000MW units, and takes the technical and economic comparison of the feed-water pump type selection. Analyzed diverse configurations of the boiler feed-water pump set. For example, to 1000MW units boiler feed-water pump set in a factory, obtained relatively optimal configuration of feed-water pump in connection with various technical and economic index.

Optical and synthetic aperture radar(SAR) image registration has become a research focus in the area of multisensory image processing for their information complementarity and feature difference.Based on the structural similarity between images,registration via implicit similarity simplifies the traditional feature matching process as a migration of the feature points and the iterative search of registration parameters on a single image.This method provides a new idea for optical and SAR image registration.As a result,the Canny operator is adopted to modify extraction process of feature points.The joint Markov model(JMM) is employed to improve denoising quality of SAR image.The search process of registration parameters is optimized with the modified quantum particle swarm optimization(QPSO) algorithm,and the optical and SAR image registration is finally realized.The experiment proves that the improved implicit similarity algorithm on optical and SAR image registration can reach a high accuracy of pixel level or even sub-pixel level.

Thermal transport measurements in multi-wall carbon nanotube (MWCNT) bundles at elevated temperatures up to 830K are reported using a novel generalized electrothermal technique. Compared with individual CNTs, the thermal conductivity (k) of MWCNT bundles is two to three orders of magnitude lower, suggesting the thermal transport in MWCNT bundles is dominated by the tube-to-tube thermal contact resistance. The effective density for the two MWCNT bundles, which is difficult to measure using other techniques, is determined at 116kg/m3 and 234kg/m3. The thermal diffusivity slightly decreases with temperature while k exhibits a small increase with temperature up to 500K and then decreases. For the first time, the behavior of specific heat for MWCNTs above room temperature is determined. The specific heat is close to graphite at 300–400K but is lower than that for graphite above 400K, indicating that the behavior of phonons in MWCNT bundles is dominated by boundary scattering rather than by the three-phonon Umklapp process. The analysis of the radiation heat loss suggests that it needs to be considered when measuring the thermophysical properties of micro/nano wires of high aspect ratios at elevated temperatures, especially for individual MWCNTs due to their extremely small diameters.

With the increase of steam turbine's steam parameter and the participation in peak-load adjustment of power grid more and more frequently, the stress of the turbine's rotor is becoming increasingly complex, and the alternating thermal stress has became the major factor reducing its life. This paper used a 600MW supercritical steam turbine's rotor as the research object, and analyzed the variation of thermal stress in the warm starting-up process. In this paper the analysis based on the operating data measured from actual operation and calculate the variations of the temperature field and stress field during the process of warm starting-up with the method of thermal-structure direct interaction analysis by Ansys. By analyzing the results, it proves that the maximum stress of the rotor is in the first stage of the intermediate pressure casing, and it is the main factor restricting the velocity of steam turbine's starting-up process. This result which calculated and analyzed by finite element method can be a theoretical basis for the optimal operation and online monitoring of turbine units.

A transient molecular dynamics technique is developed to characterize the thermophysical properties of two-dimensional graphene nanoribbons (GNRs). By directly tracking the thermal-relaxation history of a GNR that is heated by a thermal impulse, we are able to determine its thermal diffusivity quickly and accurately. We study the dynamic thermal conductivity of various length GNRs of 1.99 nm width. Quantum correction is applied in all of the temperature calculations and is found to have a critical role in the thermal-transport study of graphene. The calculated specific heat of GNRs agrees well with that of graphite at 300.6 and 692.3 K, showing little effect of the unique graphene structure on its ability to store thermal energy. A strong size effect on GNR's thermal conductivity is observed and its theoretical values for an infinite-length limit are evaluated by data fitting and extrapolation. With infinite length, the 1.99-nm-wide GNR has a thermal conductivity of 149 W m(-1) K-1 at 692.3 K, and 317 W m(-1) K-1 at 300.6 K. Our study of the temperature distribution and evolution suggests that diffusive transport is dominant in the studied GNRs. Non-Fourier heat conduction is observed at the beginning of the thermal-relaxation procedure. Thermal waves in GNR's in-plane direction are observed only for phonons in the flexural direction (ZA mode). The observed propagation speed (c = 4.6 km s(-1)) of the thermal wave follows the relation of c = v(g) / root 2 (v(g) is the ZA phonon group velocity). Our thermal-wave study reveals that in graphene, the ZA phonons transfer thermal energy much faster than longitudinal (LA) and transverse (TA) modes. Also, ZA <-> ZA energy transfer is much faster than the ZA <-> LA/TA phonon energy transfer.

In order to make the best use of existing aerial imagery and ground control points,save cost and reduce working hours,a new method of combined bundle block adjustment based on existing ground control points and multi-period aerial imagery is put forward in the paper. Firstly,the mathematical model of combined bundle block adjustment is deduced. Then the data sets of a place in South China are used to validate the proposed method. The experiment results show that the combined bundle block adjustment can deliver the effect of existing ground control points from former aerial imagery to later aerial imagery through the corresponding points among them. The plane accuracy of pass points of the combined bundle block adjustment is similar to that of the conventional bundle block adjustment. The height accuracy of pass points is dependent on the quantity of corresponding point observations among the multi-period aerial imagery. The more the corresponding point observations are,the better the height accuracy of pass points is. So as long as there are enough corresponding point observations among the multi-period aerial imagery in the same area,the accuracy of pass points derived from combined bundle block adjustment will be meet the topographic maps specifications for aerophotogrammetric operation.